3D model adaptation is usually done in a manual way, which is generally not desirable. Another way to adapt a 3D model makes use of state adaptation, which concerns the adaptation of the 3D model in order to comply with a certain state. The state affects the 3D position of the shape and/or the appearance such as the texture of certain parts or features of the model. Again a major problem with present techniques for 3D model state adaptation is that the number of features to be adapted in 3D is usually very high, such that again manual intervention is often required due to insufficient computing resources. Moreover state-of-the-art techniques are limited to using rigged models, which presents a severe limitation for use in dynamic systems where models can be learned such that their shape can also vary during the learning process.